The Design and Development of a Multi-Disciplinary Project in Embedded Systems Design

As has been noted over the past ten years, “The wall between computer science and electrical engineering has kept the potential of embedded systems at bay. It is time to build a new scientific foundation with embedded systems design as the cornerstone, which will ensure a systematic and even-handed integration of the two fields.”[1] In Baylor University’s School of Engineering & Computer Science, the Embedded Systems course in the Department of Computer Science, and the Embedded Systems Design course in the Department of Electrical and Computer Engineering have been offered independent of each other in the recent past. In the past year, however, this is beginning to change, with plans developing to combine the project portion of the two courses into one multi-disciplinary group project. This paper will document the two courses – scope and sequence, as well as emphasis, equipment used, and delivery style – highlighting the need for a new and innovative approach at the systematic integration of software and hardware in the design and development of a mutli-disciplinary group project. The beta test of this group project is occurring in the fall 2017 semester, with full first-time full-scale deployment during the spring 2018 semester. The results of this beta test will be discussed, and the lessons learned and planned modifications to the course will be considered.Cockrell School of Engineerin

A survey of visual preprocessing and shape representation techniques

Many recent theories and methods proposed for visual preprocessing and shape representation are summarized. The survey brings together research from the fields of biology, psychology, computer science, electrical engineering, and most recently, neural networks. It was motivated by the need to preprocess images for a sparse distributed memory (SDM), but the techniques presented may also prove useful for applying other associative memories to visual pattern recognition. The material of this survey is divided into three sections: an overview of biological visual processing; methods of preprocessing (extracting parts of shape, texture, motion, and depth); and shape representation and recognition (form invariance, primitives and structural descriptions, and theories of attention)

Computers from plants we never made. Speculations

We discuss possible designs and prototypes of computing systems that could be based on morphological development of roots, interaction of roots, and analog electrical computation with plants, and plant-derived electronic components. In morphological plant processors data are represented by initial configuration of roots and configurations of sources of attractants and repellents; results of computation are represented by topology of the roots' network. Computation is implemented by the roots following gradients of attractants and repellents, as well as interacting with each other. Problems solvable by plant roots, in principle, include shortest-path, minimum spanning tree, Voronoi diagram, $\alpha$-shapes, convex subdivision of concave polygons. Electrical properties of plants can be modified by loading the plants with functional nanoparticles or coating parts of plants of conductive polymers. Thus, we are in position to make living variable resistors, capacitors, operational amplifiers, multipliers, potentiometers and fixed-function generators. The electrically modified plants can implement summation, integration with respect to time, inversion, multiplication, exponentiation, logarithm, division. Mathematical and engineering problems to be solved can be represented in plant root networks of resistive or reaction elements. Developments in plant-based computing architectures will trigger emergence of a unique community of biologists, electronic engineering and computer scientists working together to produce living electronic devices which future green computers will be made of.Comment: The chapter will be published in "Inspired by Nature. Computing inspired by physics, chemistry and biology. Essays presented to Julian Miller on the occasion of his 60th birthday", Editors: Susan Stepney and Andrew Adamatzky (Springer, 2017

Integrating a nanologic knowledge module Into an undergraduate logic design course

This work discusses a knowledge module in an undergraduate logic design course for electrical engineering (EE) and computer science (CS) students, that introduces them to nanocomputing concepts. This knowledge module has a twofold objective. First, the module interests students in the fundamental logical behavior and functionality of the nanodevices of the future, which will motivate them to enroll in other elective courses related to nanotechnology, offered in most EE and CS departments. Second, this module can be used to let students analyze, synthesize, and apply their existing knowledge of the Karnaugh-map-based Boolean logic reduction scheme into a revolutionary design context with majority logic. Where many efforts focus on developing new courses on nanofabrication and even nanocomputing, this work is designed to augment the existing standard EE and CS courses by inserting knowledge modules on nanologic structures so as to stimulate student interest without creating a significant diversion from the course framework

An integrated framework to support remote IEEE 1149.1 /1149.4 design for test experiments

Remote experiments for academic purposes can only achieve their educational goals if an appropriate framework is able to provide a basic set of features, namely remote laboratory management, collaborative learning tools and content management and delivery. This paper presents a framework developed to support remote experiments in a design for test class offered to final year students at the Electrical and Computer Engineering degree at the University of Porto. The proposed solution combines a test language command interpreter and various virtual instruments (VIs), with a demonstration board that comprises a boundary-scan IEEE 1149.1 / 1149.4 test infrastructure. The experiments are presented as embedded learning objects, with no distinction from other e-learning contents (e.g. lessons, lecture notes, etc.)

Simulating a Semantic Network in LMS

Submitted to the Department of Electrical Engineering and Computer Science on January 1, 1980 in partial fulfillment of the requirements for the Degree of Bachelor of Science.A semantic network is a collection of nodes and the links between them. The nodes represent concepts, functions and entities, and the links represent relationships between varoius nodes. Any semantic network must be supplied with a language of conventions for representing knowledge as nodes and links in the network, so that storage and retrieval of knowledge can be carried out efficiently. This thesis examines two approaches to the problem of representing real-world knowledge in a computer: one designed for use on serial computers, the other design to run on a parallel network machine. The two formalisms are shown to be nearly identical, and a simulation of the parallel language in the serial language is given.MIT Artificial Intelligence Laborator

Western Multi-blotting Device - Improve the Productivity of Protein Transfer

poster abstractDr. Stanley Chien from the Department of Electrical and Computer Engineering and Dr. Hiroki Yokota from Department of Biomedical Engineering jointly formed an interdisciplinary research team for the development of new devices to improve the productivity in Biology lab experiments. Western blotting is a common procedure in many biomedical laboratories. The team has developed a novel Western blotting device that can significantly reduce the time and cost for protein transfer experiments. Specifically, it enables the transferring of proteins of various sizes simultaneously to five blotting membranes from a single gel. The other advantage of the device is the resulting membranes are not affected by the variations among gels. A US patent is pending and a company has been formed to attract funding for the commercialization of the device. A spin-off company, YCBioelectric LLC., was created with the support of IURTC for commercialization of the Western Multi-blotting device. A $300,000 NIH STTR phase I grant has been received to further develop the devi

Transfer learning by borrowing examples for multiclass object detection

Thesis (S.M.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 2012.Cataloged from PDF version of thesis.Includes bibliographical references (p. 31-33).Despite the recent trend of increasingly large datasets for object detection, there still exist many classes with few training examples. To overcome this lack of training data for certain classes, we propose a novel way of augmenting the training data for each class by borrowing and transforming examples from other classes. Our model learns which training instances from other classes to borrow and how to transform the borrowed examples so that they become more similar to instances from the target class. Our experimental results demonstrate that our new object detector, with borrowed and transformed examples, improves upon the current state-of-the-art detector on the challenging SUN09 object detection dataset.by Joseph J. Lim.S.M